from sklearn_benchmarks.report import Reporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
scikit-learn vs. scikit-learn-intelex (Intel® oneAPI) benchmarks: perfect hyperparameters match¶Reporting(config="config.yml").run()
KNeighborsClassifier: scikit-learn (1.0.dev0) vs. scikit-learn-intelex (2021.20210705.191215)¶All estimators share the following hyperparameters: algorithm=brute.
| estimator | function | n_samples_train | n_samples | n_features | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | NaN | 0.173 | 0.0 | 4.627 | 0.0 | 1 | 100 | NaN | NaN | 0.576 | 0.0 | 0.300 | 0.0 | See | See |
| 3 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | NaN | 0.148 | 0.0 | 5.391 | 0.0 | 1 | 5 | NaN | NaN | 0.563 | 0.0 | 0.263 | 0.0 | See | See |
| 6 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | NaN | 0.140 | 0.0 | 5.704 | 0.0 | 1 | 1 | NaN | NaN | 0.561 | 0.0 | 0.250 | 0.0 | See | See |
| 9 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | NaN | 0.145 | 0.0 | 5.503 | 0.0 | -1 | 100 | NaN | NaN | 0.546 | 0.0 | 0.266 | 0.0 | See | See |
| 12 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | NaN | 0.134 | 0.0 | 5.957 | 0.0 | -1 | 5 | NaN | NaN | 0.559 | 0.0 | 0.240 | 0.0 | See | See |
| 15 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | NaN | 0.153 | 0.0 | 5.216 | 0.0 | -1 | 1 | NaN | NaN | 0.563 | 0.0 | 0.272 | 0.0 | See | See |
| 18 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | NaN | 0.062 | 0.0 | 0.258 | 0.0 | 1 | 100 | NaN | NaN | 0.099 | 0.0 | 0.629 | 0.0 | See | See |
| 21 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | NaN | 0.059 | 0.0 | 0.273 | 0.0 | 1 | 5 | NaN | NaN | 0.102 | 0.0 | 0.576 | 0.0 | See | See |
| 24 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | NaN | 0.055 | 0.0 | 0.289 | 0.0 | 1 | 1 | NaN | NaN | 0.102 | 0.0 | 0.544 | 0.0 | See | See |
| 27 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | NaN | 0.073 | 0.0 | 0.220 | 0.0 | -1 | 100 | NaN | NaN | 0.107 | 0.0 | 0.679 | 0.0 | See | See |
| 30 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | NaN | 0.064 | 0.0 | 0.251 | 0.0 | -1 | 5 | NaN | NaN | 0.106 | 0.0 | 0.604 | 0.0 | See | See |
| 33 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | NaN | 0.063 | 0.0 | 0.254 | 0.0 | -1 | 1 | NaN | NaN | 0.113 | 0.0 | 0.560 | 0.0 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | NaN | 27.161 | 0.347 | 0.0 | 0.027 | 1 | 100 | 0.929 | 0.818 | 4.567 | 0.054 | 5.947 | 0.103 | See | See |
| 2 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | NaN | 0.242 | 0.006 | 0.0 | 0.242 | 1 | 100 | 1.000 | 0.000 | 0.110 | 0.003 | 2.206 | 0.078 | See | See |
| 4 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | NaN | 27.250 | 0.212 | 0.0 | 0.027 | 1 | 5 | 0.829 | 0.818 | 4.554 | 0.027 | 5.984 | 0.058 | See | See |
| 5 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | NaN | 0.236 | 0.005 | 0.0 | 0.236 | 1 | 5 | 1.000 | 0.000 | 0.113 | 0.003 | 2.086 | 0.075 | See | See |
| 7 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | NaN | 18.240 | 0.153 | 0.0 | 0.018 | 1 | 1 | 0.720 | 0.696 | 4.553 | 0.018 | 4.006 | 0.037 | See | See |
| 8 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | NaN | 0.234 | 0.007 | 0.0 | 0.234 | 1 | 1 | 1.000 | 0.000 | 0.108 | 0.004 | 2.160 | 0.098 | See | See |
| 10 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | NaN | 41.247 | 0.000 | 0.0 | 0.041 | -1 | 100 | 0.929 | 0.696 | 4.556 | 0.029 | 9.053 | 0.058 | See | See |
| 11 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | NaN | 0.225 | 0.020 | 0.0 | 0.225 | -1 | 100 | 1.000 | 0.000 | 0.112 | 0.005 | 2.014 | 0.203 | See | See |
| 13 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | NaN | 41.592 | 0.000 | 0.0 | 0.042 | -1 | 5 | 0.829 | 0.917 | 4.664 | 0.042 | 8.919 | 0.080 | See | See |
| 14 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | NaN | 0.224 | 0.016 | 0.0 | 0.224 | -1 | 5 | 1.000 | 1.000 | 0.112 | 0.002 | 2.000 | 0.149 | See | See |
| 16 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | NaN | 32.929 | 0.000 | 0.0 | 0.033 | -1 | 1 | 0.720 | 0.917 | 4.664 | 0.015 | 7.061 | 0.023 | See | See |
| 17 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | NaN | 0.219 | 0.024 | 0.0 | 0.219 | -1 | 1 | 1.000 | 1.000 | 0.108 | 0.004 | 2.028 | 0.232 | See | See |
| 19 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | NaN | 20.472 | 0.283 | 0.0 | 0.020 | 1 | 100 | 0.983 | 0.984 | 1.015 | 0.007 | 20.173 | 0.314 | See | See |
| 20 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | NaN | 0.026 | 0.001 | 0.0 | 0.026 | 1 | 100 | 1.000 | 1.000 | 0.005 | 0.000 | 5.585 | 0.377 | See | See |
| 22 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | NaN | 20.485 | 0.182 | 0.0 | 0.020 | 1 | 5 | 0.982 | 0.984 | 1.017 | 0.014 | 20.150 | 0.333 | See | See |
| 23 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | NaN | 0.025 | 0.001 | 0.0 | 0.025 | 1 | 5 | 1.000 | 1.000 | 0.005 | 0.000 | 5.167 | 0.400 | See | See |
| 25 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | NaN | 12.329 | 0.057 | 0.0 | 0.012 | 1 | 1 | 0.976 | 0.973 | 1.025 | 0.027 | 12.022 | 0.316 | See | See |
| 26 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | NaN | 0.017 | 0.001 | 0.0 | 0.017 | 1 | 1 | 1.000 | 1.000 | 0.005 | 0.000 | 3.447 | 0.384 | See | See |
| 28 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | NaN | 34.726 | 0.000 | 0.0 | 0.035 | -1 | 100 | 0.983 | 0.973 | 1.017 | 0.015 | 34.136 | 0.516 | See | See |
| 29 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | NaN | 0.035 | 0.004 | 0.0 | 0.035 | -1 | 100 | 1.000 | 1.000 | 0.005 | 0.000 | 6.765 | 0.815 | See | See |
| 31 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | NaN | 34.899 | 0.000 | 0.0 | 0.035 | -1 | 5 | 0.982 | 0.987 | 1.104 | 0.015 | 31.598 | 0.428 | See | See |
| 32 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | NaN | 0.036 | 0.005 | 0.0 | 0.036 | -1 | 5 | 1.000 | 1.000 | 0.005 | 0.001 | 7.063 | 1.148 | See | See |
| 34 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | NaN | 26.616 | 0.188 | 0.0 | 0.027 | -1 | 1 | 0.976 | 0.987 | 1.111 | 0.026 | 23.960 | 0.577 | See | See |
| 35 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | NaN | 0.024 | 0.002 | 0.0 | 0.024 | -1 | 1 | 1.000 | 1.000 | 0.005 | 0.000 | 4.743 | 0.407 | See | See |
KNeighborsClassifier_kd_tree: scikit-learn (1.0.dev0) vs. scikit-learn-intelex (2021.20210705.191215)¶All estimators share the following hyperparameters: algorithm=kd_tree.
| estimator | function | n_samples_train | n_samples | n_features | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | NaN | 2.778 | 0.0 | 0.029 | 0.0 | -1 | 5 | NaN | NaN | 0.816 | 0.0 | 3.404 | 0.0 | See | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | NaN | 2.882 | 0.0 | 0.028 | 0.0 | -1 | 100 | NaN | NaN | 0.799 | 0.0 | 3.609 | 0.0 | See | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | NaN | 3.004 | 0.0 | 0.027 | 0.0 | 1 | 5 | NaN | NaN | 0.785 | 0.0 | 3.826 | 0.0 | See | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | NaN | 3.211 | 0.0 | 0.025 | 0.0 | 1 | 100 | NaN | NaN | 0.771 | 0.0 | 4.164 | 0.0 | See | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | NaN | 3.189 | 0.0 | 0.025 | 0.0 | 1 | 1 | NaN | NaN | 0.780 | 0.0 | 4.089 | 0.0 | See | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | NaN | 3.082 | 0.0 | 0.026 | 0.0 | -1 | 1 | NaN | NaN | 0.792 | 0.0 | 3.889 | 0.0 | See | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | NaN | 0.763 | 0.0 | 0.021 | 0.0 | -1 | 5 | NaN | NaN | 0.541 | 0.0 | 1.410 | 0.0 | See | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | NaN | 0.774 | 0.0 | 0.021 | 0.0 | -1 | 100 | NaN | NaN | 0.550 | 0.0 | 1.406 | 0.0 | See | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | NaN | 0.699 | 0.0 | 0.023 | 0.0 | 1 | 5 | NaN | NaN | 0.543 | 0.0 | 1.286 | 0.0 | See | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | NaN | 0.740 | 0.0 | 0.022 | 0.0 | 1 | 100 | NaN | NaN | 0.527 | 0.0 | 1.404 | 0.0 | See | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | NaN | 0.803 | 0.0 | 0.020 | 0.0 | 1 | 1 | NaN | NaN | 0.538 | 0.0 | 1.493 | 0.0 | See | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | NaN | 0.763 | 0.0 | 0.021 | 0.0 | -1 | 1 | NaN | NaN | 0.513 | 0.0 | 1.487 | 0.0 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | NaN | 0.898 | 0.025 | 0.000 | 0.001 | -1 | 5 | 0.971 | 0.970 | 0.710 | 0.015 | 1.265 | 0.045 | See | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | NaN | 0.004 | 0.001 | 0.000 | 0.004 | -1 | 5 | 1.000 | 1.000 | 0.001 | 0.000 | 4.371 | 1.737 | See | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | NaN | 3.043 | 0.031 | 0.000 | 0.003 | -1 | 100 | 0.969 | 0.970 | 0.704 | 0.018 | 4.323 | 0.119 | See | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | NaN | 0.006 | 0.001 | 0.000 | 0.006 | -1 | 100 | 1.000 | 1.000 | 0.001 | 0.000 | 6.781 | 2.624 | See | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | NaN | 1.589 | 0.028 | 0.000 | 0.002 | 1 | 5 | 0.971 | 0.971 | 0.227 | 0.005 | 6.983 | 0.192 | See | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | NaN | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 5 | 1.000 | 1.000 | 0.000 | 0.000 | 4.469 | 2.491 | See | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | NaN | 5.170 | 0.163 | 0.000 | 0.005 | 1 | 100 | 0.969 | 0.971 | 0.233 | 0.016 | 22.218 | 1.695 | See | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | NaN | 0.003 | 0.001 | 0.000 | 0.003 | 1 | 100 | 1.000 | 1.000 | 0.000 | 0.000 | 8.391 | 4.089 | See | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | NaN | 0.830 | 0.023 | 0.000 | 0.001 | 1 | 1 | 0.951 | 0.958 | 0.129 | 0.004 | 6.456 | 0.268 | See | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | NaN | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 1.000 | 1.000 | 0.000 | 0.000 | 4.336 | 2.242 | See | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | NaN | 0.438 | 0.010 | 0.000 | 0.000 | -1 | 1 | 0.951 | 0.958 | 0.130 | 0.004 | 3.366 | 0.125 | See | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | NaN | 0.003 | 0.001 | 0.000 | 0.003 | -1 | 1 | 1.000 | 1.000 | 0.000 | 0.000 | 11.840 | 6.816 | See | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | NaN | 0.032 | 0.002 | 0.000 | 0.000 | -1 | 5 | 0.980 | 0.988 | 0.008 | 0.001 | 3.920 | 0.444 | See | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | NaN | 0.003 | 0.001 | 0.000 | 0.003 | -1 | 5 | 1.000 | 1.000 | 0.000 | 0.000 | 16.135 | 10.317 | See | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | NaN | 0.048 | 0.003 | 0.000 | 0.000 | -1 | 100 | 0.983 | 0.988 | 0.008 | 0.001 | 5.944 | 0.610 | See | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | NaN | 0.003 | 0.001 | 0.000 | 0.003 | -1 | 100 | 1.000 | 1.000 | 0.000 | 0.000 | 15.214 | 8.485 | See | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | NaN | 0.029 | 0.002 | 0.001 | 0.000 | 1 | 5 | 0.980 | 0.984 | 0.001 | 0.000 | 21.826 | 5.932 | See | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | NaN | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 5 | 1.000 | 1.000 | 0.000 | 0.000 | 4.108 | 2.204 | See | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | NaN | 0.060 | 0.001 | 0.000 | 0.000 | 1 | 100 | 0.983 | 0.984 | 0.001 | 0.000 | 45.798 | 12.211 | See | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | NaN | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 100 | 1.000 | 1.000 | 0.000 | 0.000 | 3.066 | 2.962 | See | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | NaN | 0.028 | 0.001 | 0.001 | 0.000 | 1 | 1 | 0.977 | 0.979 | 0.001 | 0.000 | 31.431 | 8.334 | See | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | NaN | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 1.000 | 1.000 | 0.000 | 0.000 | 4.598 | 2.788 | See | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | NaN | 0.029 | 0.001 | 0.001 | 0.000 | -1 | 1 | 0.977 | 0.979 | 0.001 | 0.000 | 31.800 | 10.049 | See | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | NaN | 0.003 | 0.000 | 0.000 | 0.003 | -1 | 1 | 1.000 | 1.000 | 0.000 | 0.000 | 16.588 | 8.633 | See | See |
KMeans_tall: scikit-learn (1.0.dev0) vs. scikit-learn-intelex (2021.20210705.191215)¶All estimators share the following hyperparameters: algorithm=full, n_clusters=3, max_iter=30, n_init=1, tol=1e-16.
| estimator | function | n_samples_train | n_samples | n_features | n_iter_sklearn | mean_sklearn | stdev_sklearn | throughput | latency | init | adjusted_rand_score_sklearn | n_iter_sklearnex | adjusted_rand_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 30 | 0.747 | 0.0 | 0.643 | 0.0 | k-means++ | NaN | 30 | NaN | 0.336 | 0.0 | 2.226 | 0.0 | See | See |
| 3 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 30 | 0.604 | 0.0 | 0.794 | 0.0 | random | NaN | 30 | NaN | 0.384 | 0.0 | 1.572 | 0.0 | See | See |
| 6 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 30 | 9.206 | 0.0 | 2.607 | 0.0 | k-means++ | NaN | 30 | NaN | 4.243 | 0.0 | 2.170 | 0.0 | See | See |
| 9 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 30 | 8.102 | 0.0 | 2.962 | 0.0 | random | NaN | 30 | NaN | 4.477 | 0.0 | 1.810 | 0.0 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | n_iter_sklearn | mean_sklearn | stdev_sklearn | throughput | latency | init | adjusted_rand_score_sklearn | n_iter_sklearnex | adjusted_rand_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_tall | predict | 1000000 | 1000 | 2 | 30 | 0.002 | 0.000 | 0.260 | 0.000 | k-means++ | 0.000 | 30 | 0.000 | 0.0 | 0.0 | 7.773 | 3.758 | See | See |
| 2 | KMeans_tall | predict | 1000000 | 1 | 2 | 30 | 0.002 | 0.000 | 0.000 | 0.002 | k-means++ | 1.000 | 30 | 1.000 | 0.0 | 0.0 | 10.351 | 4.568 | See | See |
| 4 | KMeans_tall | predict | 1000000 | 1000 | 2 | 30 | 0.002 | 0.000 | 0.266 | 0.000 | random | 0.000 | 30 | 0.001 | 0.0 | 0.0 | 7.822 | 3.800 | See | See |
| 5 | KMeans_tall | predict | 1000000 | 1 | 2 | 30 | 0.002 | 0.000 | 0.000 | 0.002 | random | 1.000 | 30 | 1.000 | 0.0 | 0.0 | 9.323 | 5.322 | See | See |
| 7 | KMeans_tall | predict | 1000000 | 1000 | 100 | 30 | 0.002 | 0.001 | 10.660 | 0.000 | k-means++ | 0.001 | 30 | 0.002 | 0.0 | 0.0 | 6.792 | 3.341 | See | See |
| 8 | KMeans_tall | predict | 1000000 | 1 | 100 | 30 | 0.002 | 0.000 | 0.013 | 0.002 | k-means++ | 1.000 | 30 | 1.000 | 0.0 | 0.0 | 8.529 | 5.850 | See | See |
| 10 | KMeans_tall | predict | 1000000 | 1000 | 100 | 30 | 0.002 | 0.000 | 10.986 | 0.000 | random | 0.002 | 30 | 0.001 | 0.0 | 0.0 | 6.860 | 2.831 | See | See |
| 11 | KMeans_tall | predict | 1000000 | 1 | 100 | 30 | 0.002 | 0.000 | 0.014 | 0.002 | random | 1.000 | 30 | 1.000 | 0.0 | 0.0 | 7.870 | 4.558 | See | See |
KMeans_short: scikit-learn (1.0.dev0) vs. scikit-learn-intelex (2021.20210705.191215)¶All estimators share the following hyperparameters: algorithm=full, n_clusters=300, max_iter=20, n_init=1, tol=1e-16.
| estimator | function | n_samples_train | n_samples | n_features | n_iter_sklearn | mean_sklearn | stdev_sklearn | throughput | latency | init | adjusted_rand_score_sklearn | n_iter_sklearnex | adjusted_rand_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | fit | 10000 | 10000 | 2 | 20 | 0.334 | 0.0 | 0.010 | 0.0 | k-means++ | NaN | 20 | NaN | 0.055 | 0.0 | 6.047 | 0.0 | See | See |
| 3 | KMeans_short | fit | 10000 | 10000 | 2 | 20 | 0.106 | 0.0 | 0.030 | 0.0 | random | NaN | 20 | NaN | 0.144 | 0.0 | 0.733 | 0.0 | See | See |
| 6 | KMeans_short | fit | 10000 | 10000 | 100 | 20 | 1.202 | 0.0 | 0.133 | 0.0 | k-means++ | NaN | 20 | NaN | 0.281 | 0.0 | 4.273 | 0.0 | See | See |
| 9 | KMeans_short | fit | 10000 | 10000 | 100 | 20 | 0.360 | 0.0 | 0.444 | 0.0 | random | NaN | 20 | NaN | 0.643 | 0.0 | 0.560 | 0.0 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | n_iter_sklearn | mean_sklearn | stdev_sklearn | throughput | latency | init | adjusted_rand_score_sklearn | n_iter_sklearnex | adjusted_rand_score_sklearnex | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_short | predict | 10000 | 1000 | 2 | 20 | 0.002 | 0.0 | 0.142 | 0.000 | k-means++ | 0.002 | 20 | 0.002 | 0.001 | 0.0 | 2.994 | 0.445 | See | See |
| 2 | KMeans_short | predict | 10000 | 1 | 2 | 20 | 0.002 | 0.0 | 0.000 | 0.002 | k-means++ | 1.000 | 20 | 1.000 | 0.000 | 0.0 | 8.272 | 3.770 | See | See |
| 4 | KMeans_short | predict | 10000 | 1000 | 2 | 20 | 0.002 | 0.0 | 0.138 | 0.000 | random | 0.001 | 20 | 0.003 | 0.001 | 0.0 | 2.887 | 0.565 | See | See |
| 5 | KMeans_short | predict | 10000 | 1 | 2 | 20 | 0.002 | 0.0 | 0.000 | 0.002 | random | 1.000 | 20 | 1.000 | 0.000 | 0.0 | 9.768 | 4.044 | See | See |
| 7 | KMeans_short | predict | 10000 | 1000 | 100 | 20 | 0.003 | 0.0 | 4.647 | 0.000 | k-means++ | 0.288 | 20 | 0.375 | 0.002 | 0.0 | 1.903 | 0.355 | See | See |
| 8 | KMeans_short | predict | 10000 | 1 | 100 | 20 | 0.002 | 0.0 | 0.008 | 0.002 | k-means++ | 1.000 | 20 | 1.000 | 0.000 | 0.0 | 8.094 | 3.898 | See | See |
| 10 | KMeans_short | predict | 10000 | 1000 | 100 | 20 | 0.004 | 0.0 | 4.389 | 0.000 | random | 0.322 | 20 | 0.301 | 0.002 | 0.0 | 2.196 | 0.338 | See | See |
| 11 | KMeans_short | predict | 10000 | 1 | 100 | 20 | 0.002 | 0.0 | 0.008 | 0.002 | random | 1.000 | 20 | 1.000 | 0.000 | 0.0 | 7.780 | 3.635 | See | See |
LogisticRegression: scikit-learn (1.0.dev0) vs. scikit-learn-intelex (2021.20210705.191215)¶All estimators share the following hyperparameters: penalty=l2, dual=False, tol=0.0001, C=1.0, fit_intercept=True, intercept_scaling=1, class_weight=nan, random_state=nan, solver=lbfgs, max_iter=100, multi_class=auto, verbose=0, warm_start=False, n_jobs=nan, l1_ratio=nan.
| estimator | function | n_samples_train | n_samples | n_features | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | class_weight | l1_ratio | n_jobs | random_state | accuracy_score | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 1000000 | 1000000 | 100 | [20] | 17.538 | 0.0 | [-0.06727524] | 0.000 | NaN | NaN | NaN | NaN | NaN | 3.170 | 0.0 | 5.533 | 0.0 | See | See |
| 3 | LogisticRegression | fit | 1000 | 1000 | 10000 | [26] | 1.434 | 0.0 | [1.45037389] | 0.001 | NaN | NaN | NaN | NaN | NaN | 1.417 | 0.0 | 1.012 | 0.0 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | class_weight | l1_ratio | n_jobs | random_state | accuracy_score | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | LogisticRegression | predict | 1000000 | 1000 | 100 | [20] | 0.000 | 0.0 | [41.59640774] | 0.0 | NaN | NaN | NaN | NaN | 0.541 | 0.000 | 0.0 | 0.872 | 0.398 | See | See |
| 2 | LogisticRegression | predict | 1000000 | 1 | 100 | [20] | 0.000 | 0.0 | [0.12016568] | 0.0 | NaN | NaN | NaN | NaN | 1.000 | 0.000 | 0.0 | 0.449 | 0.320 | See | See |
| 4 | LogisticRegression | predict | 1000 | 100 | 10000 | [26] | 0.003 | 0.0 | [79.58656006] | 0.0 | NaN | NaN | NaN | NaN | 0.310 | 0.004 | 0.0 | 0.656 | 0.094 | See | See |
| 5 | LogisticRegression | predict | 1000 | 1 | 10000 | [26] | 0.000 | 0.0 | [13.64994198] | 0.0 | NaN | NaN | NaN | NaN | 1.000 | 0.001 | 0.0 | 0.160 | 0.071 | See | See |
Ridge: scikit-learn (1.0.dev0) vs. scikit-learn-intelex (2021.20210705.191215)¶All estimators share the following hyperparameters: alpha=1.0, fit_intercept=True, normalize=deprecated, copy_X=True, max_iter=nan, tol=0.001, solver=auto, random_state=nan.
| estimator | function | n_samples_train | n_samples | n_features | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | max_iter | random_state | r2_score | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 1000 | 1000 | 10000 | NaN | 0.344 | 0.0 | 0.232 | 0.0 | NaN | NaN | NaN | 0.341 | 0.0 | 1.009 | 0.0 | See | See |
| 3 | Ridge | fit | 1000000 | 1000000 | 100 | NaN | 1.836 | 0.0 | 0.436 | 0.0 | NaN | NaN | NaN | 0.429 | 0.0 | 4.278 | 0.0 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | max_iter | random_state | r2_score | mean_sklearnex | stdev_sklearnex | speedup | stdev_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Ridge | predict | 1000 | 1000 | 10000 | NaN | 0.012 | 0.001 | 6.457 | 0.0 | NaN | NaN | 0.115 | 0.023 | 0.002 | 0.551 | 0.047 | See | See |
| 2 | Ridge | predict | 1000 | 1 | 10000 | NaN | 0.000 | 0.000 | 0.630 | 0.0 | NaN | NaN | NaN | 0.000 | 0.000 | 0.694 | 0.562 | See | See |
| 4 | Ridge | predict | 1000000 | 1000 | 100 | NaN | 0.000 | 0.000 | 3.848 | 0.0 | NaN | NaN | 1.000 | 0.000 | 0.000 | 0.622 | 0.349 | See | See |
| 5 | Ridge | predict | 1000000 | 1 | 100 | NaN | 0.000 | 0.000 | 0.007 | 0.0 | NaN | NaN | NaN | 0.000 | 0.000 | 0.717 | 0.605 | See | See |